Journal Information
Vol. 96. Issue 3.
Pages 196-202 (01 March 2022)
Visits
...
Vol. 96. Issue 3.
Pages 196-202 (01 March 2022)
Original Article
Open Access
Quality of life related to health and habits: Differences between adolescents in rural and urban environments
Hábitos y calidad de vida relacionada con la salud: diferencias entre adolescentes de entornos rurales y urbanos
Visits
...
Raúl Jiménez Boraitaa,
Corresponding author
rauljbcity@gmail.com

Corresponding author.
, Daniel Arriscado Alsinab, Esther Gargallo Ibortb, Josep María Dalmau Torresb
a Universidad de La Rioja, Logroño, La Rioja, Spain
b Departamento de Ciencias de la Educación, Universidad de La Rioja, Logroño, La Rioja, Spain
Article information
Abstract
Full Text
Bibliography
Download PDF
Statistics
Tables (4)
Table 1. General characteristics of the sample by type of residential setting.
Table 2. Health-related quality of life by type of residential setting.
Table 3. Level of physical activity by type of residential setting.
Table 4. Adherence to Mediterranean diet by residential setting.
Show moreShow less
Abstract
Introduction

Adolescence is a decisive stage in human development in which intense physical, psychological, emotional and social changes are experienced. There are many influential factors in health, highlighting among them the environment.

Objective

The objective of the study was to analyse the lifestyle differences associated with the health of adolescents as a function of rural and urban environment.

Methods

A cross-sectional study was conducted with a sample of 761 students (14.51 ± 1.63 years) from 25 educational centers in a region of northern Spain, distributed between 650 urban and 111 rural students. Life habits and different indicators of physical, psychological and social health were evaluated, assessing the level of physical activity, maximum oxygen consumption, hours of night sleep, quality of life related to health, self-esteem, adherence to the Mediterranean diet, the environment and the socioeconomic level.

Results

Adolescents in rural areas reported a greater number of hours of night sleep and higher levels of HRQL, both as a whole, and specifically in psychological well-being, school environment and autonomy and parents. Adolescents in urban areas reported higher levels of physical activity between 6:00 p.m. and 10:00 p.m., and a higher consumption of fast food.

Conclusions

The results show the need for strategies aimed at counteracting the negative influence that physical and sociodemographic factors typical of urbanized areas exert on HRQL. On the other hand, in relation to lifestyle habits, a wider range of extracurricular physical activities in rural areas would be recommended.

Keywords:
Rural
Urban
Quality of life
Adolescent
Habits
Health
Environment
Resumen
Introducción

La adolescencia es una etapa decisiva en el desarrollo humano en la que se experimentan intensos cambios físicos, psicológicos, emocionales y sociales. Existen multitud de factores influyentes en la salud, destacando entre ellos el entorno.

Objetivo

El objetivo del estudio fue analizar las diferencias en el estilo de vida y diversos indicadores de salud psicológica, física y social de los adolescentes en función del entorno rural y urbano.

Métodos

Se realizó un estudio trasversal en una muestra de 761 estudiantes (14,51 ± 1,63 años) de 25 centros educativos de una región del norte de España, distribuidos en 650 alumnos urbanos y 111 rurales. Se evaluaron los hábitos de vida y diferentes indicadores de salud física, psicológica y social, valorando el nivel de actividad física, el consumo máximo de oxígeno, las horas de sueño nocturno, la calidad de vida relacionada con la salud (CVRS), la autoestima, la adherencia a la dieta mediterránea, el entorno ambiental y el nivel socioeconómico.

Resultados

Los adolescentes de zonas rurales reportaron un mayor número de horas de sueño nocturno y mayores niveles de CVRS, tanto en su conjunto, como de forma específica en el bienestar psicológico, entorno escolar y autonomía y padres. Los adolescentes de zonas urbanas mostraron mayores niveles de actividad física entre las 18:00 a 22:00, y un mayor consumo de comida rápida.

Conclusiones

Los resultados manifiestan la necesidad de estrategias dirigidas a contrarrestar la influencia negativa que los factores físicos y sociodemográficos propios de las zonas urbanizadas ejercen en la CVRS. Por otro lado, en relación con los hábitos de vida, sería recomendable una oferta más amplia de actividades físicas extraescolares en las zonas rurales.

Palabras clave:
Rural
Urbano
Calidad de vida
Adolescente
Hábitos
Salud
Entorno
Full Text
Introduction

Adolescence is considered a key stage in personality development and in the consolidation of lifestyle habits, during which emerging changes at the psychological, biological, physical and social levels increase the risk of acquiring habits deleterious to health.1 Therefore, supporting the development of healthy habits is key to the prevention of health problems.2 In this context, the stage of adolescence has attracted considerable interest, with multiple studies devoted to the investigation of the most influential factors. Thus, multiple aspects, such as socioeconomic status, lifestyle habits and genetic, environmental, social and psychological factors are known determinants of health.3,4 Given this, for each of these determinants, it would be interesting to compare health status and habits in adolescents living in rural versus urban areas, since there is little evidence on the subject.

The concepts of rural setting and urban setting have been defined from different perspectives, taking into account quantitative criteria (population ranges), qualitative criteria (population density or type of economic activity) or subjective criteria (perception of inhabitants or their residential setting).5 Based on Eurostat data for 2019,6 63.32% of the population of Spain resides in predominantly urban areas, 33.31% in intermediate areas and 3.37% in rural areas, revealing substantial heterogeneity in residential settings. In relation to this, the differences between rural and urban environments in the access to sports facilities, fast food restaurants, transportation systems and living conditions can have a direct impact on the adherence to certain lifestyles, which in turn can have a direct impact on physical activity (PA) and adherence to a healthy diet.7,8 When it comes to quality of life, it seems to be influenced by physical factors such as pollution, the environment, decreased access to nature, public spaces and population density, as well as social factors such as the fast pace of life, stress and social isolation, all of which are more likely to affect residents of urban areas.9–11

A majority of studies on the differences between rural and urban areas have performed partial analyses of health determinants, with few studies taking a comprehensive approach to this issue. Thus, the objective of our study was to analyse the differences between adolescents residing in rural and urban areas in a region in northern Spain from a comprehensive health perspective. To this end, we assessed lifestyle habits and different indicators of physical, psychological and social health, the level of PA, the maximal oxygen update, night-time sleep duration, health-related quality of life (HRQoL), self-esteem, adherence to the Mediterranean diet, environmental variables and socioeconomic status (SES).

Material and methodsStudy design and participants

We conducted a cross-sectional study in a sample of students enrolled in years 1 and 4 of compulsory secondary education (“educación secundaria obligatoria”, ESO) in schools in the region of La Rioja in northern Spain. We used single-stage cluster sampling in which the units were all the classes of the selected years. Given the study universe (3470 students in year 1 of the ESO and 2548 in year 4 of the ESO), we calculated the sample size required to obtain a representative sample for each school year with a 95% level of confidence and a precision of 5%, for an expected proportion of 0.50. With these parameters, we estimated that the sample would be representative by including at least 346 students in year 1 and 334 students in year 4. Since each class had a mean of 25 students in both years, and having increased the required sample size according to the expected participation rate of 60%, we randomly selected 23 year 1 classes and 22 year 4 classes to obtain a representative sample.

We invited every student in each selected class to participate in the study, and 82% agreed to participate, the final sample included 761 adolescents in 45 classes in 25 schools, 383 in year 1 and 378 in year 4. The age of participants ranged from 12 to 17 years (mean, 14.51; standard deviation [SD], ±1.63), 49.7% were female and 50.3% male. We classified residential setting (urban vs rural) based on the number of inhabitants, considering townships with fewer than 5000 inhabitants rural.12 Based on this definition, 85.4% of participants resided in urban areas and 14.6% in rural areas.

Procedure

We obtained written informed consent from the parents or legal guardians of participants. Adolescents participated in the study on a voluntary basis after providing verbal assent. The study adhered to the ethical principles of the Declaration of Helsinki. In addition, the study was approved by the Clinical Research Ethics Committee of La Rioja. The research team conducted the fieldwork during regular school hours and applying a standardised study protocol in every class: self-administered questionnaire, anthropometric measurements and fitness test. The data collection period ranged from January to June 2018.

Instruments

We measured HRQoL with the KIDSCREEN-27 questionnaire version validated in the adolescent population of Spain.13 It comprises 27 items rated on a Likert scale and grouped in 5 dimensions: physical well-being, psychological well-being, autonomy & parents, school environment and peers & social support. We interpreted the data as directed by the developers of the test, with higher scores indicative of more positive perceptions of HRQoL.

We assessed self-esteem with the Rosenberg Self-Esteem scale, also validated in Spanish adolescents.14 It comprises 10 items with answers rated 1–4 and yields a total score ranging from 10 to 40, with higher scores indicative of greater self-esteem.

We assessed the level of PA by means of the Physical Activity Questionnaire for Adolescents (PAQ-A) adapted and validated for the adolescent population of Spain.15 This instrument assesses PA in the past 7 days with items scored on a scale from 1 to 5, with higher scores corresponding to higher levels of PA. We also added 2 items to assess participation in organised extracurricular sports and whether participants engaged in physical activity on their way to and from school (“Do you practice any extracurricular sports after school?” and “Are you physically active on your way to school? (go to school walking, on a bicycle, on skates…?”). To calculate the total hours of night-time sleep, we asked adolescents which time they went to bed and which time they woke up.

Adherence to the Mediterranean diet was assessed by means of the KIDMED questionnaire.16 It comprises 16 items that assess Mediterranean diet patterns with a dichotomous yes/no answer. The possible score ranges from –4 to 12, and higher scores reflect greater adherence to Mediterranean diet.

We evaluated environmental factors related to PA through the Assessing Levels of PHysical Activity and fitness at population level (ALPHA) environmental questionnaire, validated for use in Spanish youth.17 This questionnaire assesses the perception of factors in the immediate environment (within an approximate 1.5 km radius from the home) that may affect performance of PA, such as: type and location of the home, access to facilities and materials to engage in PA in the home and immediate environment, proximity of services, traffic and neighbourhood safety. The total score is obtained from adding up the scores in the 10 items, and higher scores represent an environment that is more conducive to performance of PA.

Socioeconomic status was assessed with the Family Affluence Scale III,18 which comprises 6 items relating to the material resources and property of the family. The score ranges from 0 and 13, with 13 corresponding to the highest level of wealth.

In addition, we used the Oviedo infrequency scale (INF-OV)19 to identify and exclude from the analysis those questionnaires that had been completed randomly, with non-random patterned responding or dishonestly. It is a self-report instrument consisting of questions with obvious answers given in a dichotomous format (0 = yes; 1 = no). We inserted 6 INF-OV items alternating with regular questionnaire items. We excluded participants with more than 1 illogical answer to these items, which turned out to be 2 of the total.

We measured height with a Holtain® stadiometer (Holtain Ltd., Dyfed, United Kingdom) accurate to 1 mm and body weight with a SECA® scale (model 713; Hamburg, Germany) accurate to 0.1 kg. We subsequently calculated the BMI and classified it according to the World Health Organization growth reference data (normal weight, overweight and obesity).20

To assess aerobic capacity, we used the Course-Navette test. We drew two transversal lines at a distance of 20 m marking the beginning and end of the path for a run. Participants had to run between both lines at a pace determined by a sequence of beeps. The beeps set a pace of 8.5 km/h at the beginning of the run and increased it by 0.5 km/h each minute. For each participant, the test ended when the participant stopped or could not complete the path at the established pace 2 consecutive times. We used the resulting data to calculate the maximal oxygen uptake (VO2 max) using the formula developed by the author of the test.21

Statistical analysis

We have summarised quantitative data as mean and standard deviation, and qualitative data as frequency distributions. We used the Kolmogorov-Smirnov test to assess the normality of the distribution and the Levene test to assess the homogeneity of variance. We compared quantitative data with the Student t test in case of a normal distribution and otherwise with the Mann-Whitney U test. We used the chi square test to assess the association between qualitative variables. The statistical analysis was performed with the software SPSS Statistics version 25.00 (IBM Corp; Chicago, IL, USA). Statistical significance was defined as a p-value of less than 0.05.

Results

Table 1 presents the results of the analysis of environmental factors, SES, PA and VO2 max, HRQoL, self-esteem, hours of sleep, diet and body mass index in urban vs rural settings. We found significantly higher HRQoL scores and greater duration of night-time sleep in students that lived in rural areas.

Table 1.

General characteristics of the sample by type of residential setting.

  Urban (n = 650)Rural (n = 111)P 
  Mean  SD  Mean  SD   
Environment  31.76  3.34  31.24  3.82  0.192 
Socioeconomic status  9.04  2.05  8.88  2.12  0.465 
Physical activity  2.61  0.61  2.58  0.63  0.975 
Maximal oxygen uptake  44.19  6.87  44.64  6.65  0.724 
Health-related quality of life  249.23  33.11  255.27  33.29  0.024 
Self-esteem  32.76  4.82  32.31  5.57  0.705 
Hours of night-time sleep  8.28  0.89  8.83  0.94  <0.001 
Adherence to Mediterranean diet  7.32  2.11  7.22  0.13  0.593 
Body mass index  21.05  3.20  2.78  2.57  0.274 

SD, standard deviation.

Table 2 summarises the results obtained for HRQoL, overall and in its 5 dimensions. Adolescents in urban areas scored significantly lower in overall HRQoL. Specifically, adolescents in urban areas scored significantly lower in the psychological well-being, school environment and autonomy & parents dimensions.

Table 2.

Health-related quality of life by type of residential setting.

  Urban (n = 650)Rural (n = 111)P 
  Mean  SD  Mean  SD   
Health-related quality of life  249.23  33.11  255.27  33.29  0.024 
Physical well-being  45.59  8.84  45.50  8.07  0.704 
Psychological well-being  49.92  9.25  51.59  9.92  0.025 
School environment  49.38  9.28  51.46  9.63  0.044 
Autonomy & parents  50.75  8.57  53.28  9.20  0.005 
Peers & social support  53.59  9.36  53.43  9.13  0.967 

SD, standard deviation.

Table 3 presents the level of PA overall and at different times of day and of the week. Although we did not find significant differences in the overall level of PA, we did find that urban adolescents were more likely to be active in the evening, between 6 pm and 10 pm. Active travel to school and participation in organised extracurricular sports activities were also more frequent in urban adolescents (71.7% vs 60.4% of rural adolescents).

Table 3.

Level of physical activity by type of residential setting.

  Urban (n = 650)Rural (n = 111)P 
  Mean  SD  Mean  SD   
Level of physical activity  2.61  0.61  2.58  0.63  0.845 
List of weekly activities  1.43  0.28  1.43  0.28  0.934 
Physical education  4.00  0.86  3.85  1.01  0.246 
Recess  2.17  1.04  2.52  1.42  0.076 
Lunch  1.47  0.81  1.60  0.93  0.208 
Afternoon (14−18 h)  2.71  1.23  2.85  1.26  0.260 
Evening (18−22 h)  3.00  1.21  2.77  1.14  0.050 
Weekend  2.66  1.05  2.60  1.06  0.850 
Weekly level of activity  2.66  1.08  2.63  1.12  0.809 
Daily frequency  2.95  0.78  2.92  0.79  0.700 

SD, standard deviation.

Lastly, Table 4 presents the results of the assessment of adherence to the Mediterranean diet. We did not find differences in overall adherence, but found a higher frequency of fast food consumption in urban adolescents.

Table 4.

Adherence to Mediterranean diet by residential setting.

  Urban (n = 650)  Rural (n = 111)  P 
  % yes  % yes   
Adherence to Mediterranean, diet mean ± SD  7.32 ± 2.11  7.22 ± 2.13  0.593 
Breakfast daily  94.50  93.07  0.746 
Dairy at breakfast  87.10  87.40  0.928 
Cereal products at breakfast  80.90  80.20  0.854 
Industrial baked goods at breakfast  19.20  25.20  0.145 
Fruit or natural fruit juice daily  67.50  65.80  0.713 
Second piece of fruit daily  49.70  45.00  0.365 
Second dairy serving daily  72.60  73.90  0.783 
Fresh (salad) or cooked vegetables daily  73.20  70.30  0.517 
Fresh or cooked vegetables more than once daily  34.00  25.20  0.069 
Fish (at least 2−3 times a week)  64.50  66.70  0.653 
Nuts (at least 2−3 times a week)  46.60  53.20  0.202 
Fast food meals (at least once a week)  20.90  11.70  0.024 
Legumes (more than once a week)  83.70  86.50  0.457 
Pasta or rice (more than 4 times a week)  38.90  38.70  0.971 
Candy or sweets (several times a day)  19.10  23.40  0.287 
Olive oil used for cooking at home  98.00  95.50  0.109 

SD, standard deviation.

Discussion

In our study, HRQoL scores were significantly higher in adolescents living in rural areas, which was consistent with the findings of studies at the international level.22 In addition, the analysis of the different dimensions of HRQoL revealed that adolescents in rural areas scored significantly higher in the psychological well-being, school environment and autonomy & parents dimensions. When it comes to psychological well-being, it is believed that the risk of developing mental health problems and psychiatric disorders is higher in urban areas.23 These disorders seem to be influenced by physical factors (pollution, population density, type of home or residential setting) and social factors (stress, social isolation, pace of life) that may be less favourable in urban areas, which could explain our findings.9,10 In addition, the type of setting and the characteristics of the immediate environment (greenery, parks and water bodies),11 the perceived air pollution or having contact with nature on a regular basis are also associated with HRQoL.24

Adolescents in urban areas also scored lower in the school environment dimension. The previous literature shows that adolescents in urban areas are more likely to experience academic anxiety, which has an impact on the relationship of students to the school environment.25 The perception of belonging to the school also seems to be weaker in urban areas, reflecting social rejection and problems with peers and instructors.26 The higher frequency of bullying and greater insecurity in urban schools,27 combined with a lesser participation in school activities, could also have a negative impact on school adjustment.28

When it came to the autonomy & parents dimension, the lower score of adolescents in urban areas may be due to higher levels of conflict in urban households.29 Thus, a lower level of attachment to the family is associated with a higher probability of behavioural and psychiatric disorders in adolescents30 and has a deleterious impact on family cohesion.

When it came to the level of PA, we did not find differences in the overall frequency of PA, but found that PA was significantly more frequent in adolescents in urban areas in the 6 pm to 10 pm time range. The lower frequency of sports activities in the rural population could be due to a lack of recreational facilities and the smaller range of athletic activities offered in rural townships.7 In addition, the aforementioned time range is when organised extracurricular sports activities are most likely to take place, which may justify the greater frequency of extracurricular sports in urban adolescents. Similarly, adolescents in urban areas have access to transportation systems that make it easier to travel to recreational facilities to engage in PA.31

The analysis of night-time sleep revealed that adolescents in rural areas slept more hours at night. This was consistent with the findings of Yang et al.,32 who found a higher prevalence of sleep disorders in the urban population and identified living in an urban area, poor parental sleep hygiene and low parental educational attainment as predictors of poor sleep in adolescents. Other aspects, like the use of mobile phones and computers, which seems significantly higher in urban populations,33 and noise and other environmental factors34 may also contribute to the observed differences.

As regards adherence to the Mediterranean diet, we did not find significant differences in overall adherence, an aspect on which results in the previous literature have been contradictory.16,35 Still, we did find a significantly higher frequency of fast food consumption in adolescents in urban areas. Factors that may have contributed to the higher frequency of fast food restaurant patronage by urban adolescents are the greater density of fast food restaurants and the closer proximity to the home in urban areas.36

There are limitations to our study, as there were fewer participants from rural settings compared to urban settings. Although this resulted from the relative proportions of the population under study, the lower frequency of rural participants could have affected some of the results, and in future research, it may be beneficial to recruit larger samples in rural settings. Another limitation is that some of the results were obtained through the use of self-report instruments, which may be a source of bias due to their subjective nature. Thus, a possible improvement in the future could be the use of accelerometers or food diaries to obtain more objective data. Nevertheless, the validity and reliability of these instruments have been demonstrated in previous studies conducted in similar populations. Lastly, we were unable to establish causality due to the cross-sectional design of the study, and performance of longitudinal studies could help interpret the observed differences.

Adolescents in rural areas reported longer duration of sleep and scored higher in HRQoL, overall and in the psychological well-being, school environment and autonomy & parents dimensions. The lower scores found in the urban population evince the need to implement strategies to counteract the deleterious impact on HRQoL of the physical and sociodemographic characteristics of these areas: noise, contamination, fast pace, etc. On the other hand, when it came to lifestyle habits, while we did not find overall differences in PA and adherence to the Mediterranean diet, we found that adolescents in urban areas consumed more fast food and tended to engage in PA later in the day, between 6 pm and 10 pm. In light of this, it would be beneficial to offer a wider range of extracurricular athletic activities in rural areas among other efforts to bridge this gap.

Funding

This study was partially funded by the Instituto de Estudios Riojanos (IER) of the Government of La Rioja through resolution no. 55/2018, of 9 July of the Administration of the IER for the awarding of research grants focused on La Rioja for the 2018–2019 period.

Conflicts of interest

The authors have no conflicts of interest to declare.

References
[1]
S.F. Hamilton, M.A. Hamilton.
The youth development handbook: coming of age in American communities.
1st ed., Sage Publications, (2004),
[2]
W. Meeus.
Adolescent development: longitudinal research into the self, personal relationships and psychopathology.
1st ed., Routledge, (2018),
[3]
I. Seiffge-Krenke.
Adolescents’ health: a developmental perspective.
1st ed., Psychology Press, (2019),
[4]
R. Jessor, M.S. Turbin, F.M. Costa.
The role of protection in adolescent health behavior.
Problem behavior theory and adolescent health, Springer Cham, (2017), pp. 549-574
[5]
G.P.V. Peña, G.J.P.C. Medina, G.S.G. Mora.
Urbano-rural, constante búsqueda de fronteras conceptuales.
Rev Inf An, 20 (2002), pp. 17-24
[6]
Eurostat regional yearbook, 2019 edition, Publication Office of the European Union, (2019),
[7]
R. Hoekman, K. Breedveld, G. Kraaykamp.
Sport participation and the social and physical environment: explaining differences between urban and rural areas in the Netherlands.
Leisure Stud, 36 (2017), pp. 357-370
[8]
J. Wang, M. Williams, E. Rush, N. Crook, N.G. Forouhi, D. Simmons.
Mapping the availability and accessibility of healthy food in rural and urban New Zealand–Te Wai o Rona: Diabetes Prevention Strategy.
Public Health Nutr, 13 (2010), pp. 1049-1055
[9]
O. Gruebner, M.A. Rapp, M. Adli, U. Kluge, S. Galea, A. Heinz.
Cities and mental health.
Dtsch Ärztebl Int, 114 (2017), pp. 121
[10]
M.A. Beenackers, J.O. Groeniger, C.B. Kamphuis, F.J. Van Lenthe.
Urban population density and mortality in a compact Dutch city: 23-year follow-up of the Dutch GLOBE study.
[11]
S. Tillmann, A.F. Clark, J.A. Gilliland.
Children and nature: linking accessibility of natural environments and children’s health-related quality of life.
Int J Environ Res Public Health, 15 (2018), pp. 1072
[12]
Ministerio de Medio Ambiente y Medio Rural y Marino. Población y sociedad rural. Análisis y prospectiva-Serie AgrInfo n.°12. Subdirección General de Análisis, Prospectiva y Coordinación, Subsecretaría. Ministerio de Medio Ambiente y Medio Rural y Marino; 2009.
[13]
M. Aymerich, S. Berra, I. Guillamón, M. Herdman, J. Alonso, U. Ravens, L. Rajmil.
Desarrollo de la versión en español del KIDSCREEN: un cuestionario de calidad de vida para la población infantil y adolescente.
Gac Sanit, 19 (2005), pp. 93-102
[14]
F.L. Atienza, Y. Moreno, I. Balaguer.
Análisis de la dimensionalidad de la Escala de Autoestima de Rosenberg en una muestra de adolescentes valencianos.
Rev Psicol, 22 (2000), pp. 29-42
[15]
D. Martínez, V. Martínez de Haro, T. Pozo, G.J. Welk, A. Villagra, M.E. Calle, et al.
Fiabilidad y validez del cuestionario de actividad física PAQ-A en adolescentes españoles.
Rev Esp Salud Pública, 83 (2009), pp. 427-439
[16]
L. Serra, L. Ribas, J. Ngo, R.M. Ortega, A. García, C. Pérez, et al.
Food, youth and the Mediterranean diet in Spain. Development of KIDMED, Mediterranean Diet Quality Index in children and adolescents.
Public Health Nutr, 7 (2004), pp. 931-935
[17]
L. García-Cervantes, D. Martinez-Gomez, G. Rodríguez-Romo, V. Cabanas-Sánchez, A. Marcos, ÓL. Veiga.
Reliability and validity of an adapted version of the ALPHA environmental questionnaire on physical activity in Spanish youth.
Nutr Hosp, 30 (2014), pp. 1118-1124
[18]
J.E.K. Hartley, K. Levin, C. Currie.
A new version of the HBSC Family Affluence Scale-FAS III: Scottish Qualitative Findings from the International FAS Development Study.
Child Indic Res, 9 (2016), pp. 233-245
[19]
E. Fonseca, M. Paíno, S. Lemos, Ú. Villazón, J. Muñiz.
Validation of the schizotypal personality questionnaire brief form in adolescents.
Schizophr Res, 111 (2009), pp. 53-60
[20]
M.D. Onis, A.W. Onyango, E. Borghi, A. Siyam, C. Nishida, J. Siekmann.
Development of a WHO growth reference for school-aged children and adolescents.
Bull World Health Organ, 85 (2007), pp. 660-667
[21]
L.A. Leger, D. Mercier, C. Gadoury, J. Lambert.
The multistage 20 metre shuttle run test for aerobic fitness.
J Sports Sci, 6 (1988), pp. 93-101
[22]
K.A. Bolton, F. Jacka, S. Allender, P. Kremer, L. Gibbs, E. Waters, A. De Silva.
The association between self‐reported diet quality and health‐related quality of life in rural and urban Australian adolescents.
Aust J Rural Health, 24 (2016), pp. 317-325
[23]
E. Vassos, E. Agerbo, O. Mors, C.B. Pedersen.
Urban–rural differences in incidence rates of psychiatric disorders in Denmark.
Br J Psychiatry, 208 (2016), pp. 435-440
[24]
A. Cárceles, J.A. Ortega, F.A. López, J.L. Fuster, A. Sanz, R. Ramis, L. Claudio.
Environment, lifestyle behavior and health-related quality of life in childhood and adolescent cancer survivors of extracranial malignancies.
Environ Res, 189 (2020),
[25]
S. Kohli, A. Malik.
Academic anxiety and wellbeing amongst rural and urban adolescents.
Indian J Positive Psychol, 4 (2013), pp. 148
[26]
E.M. Anderman.
School effects on psychological outcomes during adolescence.
J Educ Psychol, 94 (2002), pp. 795
[27]
E.M. Anderman, D.M. Kimweli.
Victimization and safety in schools serving early adolescents.
J Early Adolesc, 17 (1997), pp. 408-438
[28]
L.R. Stanley, M.L.G. Comello, R.W. Edwards, B.S. Marquart.
School adjustment in rural and urban communities: Do students from “Timbuktu” differ from their “City Slicker” peers?.
J Youth Adolesc, 37 (2008), pp. 225-238
[29]
W. Zhang, A.J. Fuligni.
Authority, autonomy, and family relationships among adolescents in urban and rural China.
J Res Adolesc, 16 (2006), pp. 527-537
[30]
J. Oldfield, N. Humphrey, J. Hebron.
The role of parental and peer attachment relationships and school connectedness in predicting adolescent mental health outcomes.
Child Adolesc Mental Health, 21 (2016), pp. 21-29
[31]
C.A. Loucaides, S.M. Chedzoy, N. Bennett.
Differences in physical activity levels between urban and rural school children in Cyprus.
Health Educ Res, 19 (2004), pp. 138-147
[32]
Q.Z. Yang, Y.Q. Bu, S.Y. Dong, S.S. Fan, L.X. Wang.
A comparison of sleeping problems in school‐age children between rural and urban communities in China.
J Paediatr Child Health, 45 (2009), pp. 414-418
[33]
J. Dollman, C. Maher, T.S. Olds, K. Ridley.
Physical activity and screen time behaviour in metropolitan, regional and rural adolescents: a-sectional study of Australians aged 9–16 years.
J Sci Med Sport, 15 (2012), pp. 32-37
[34]
S. Sofyani, S. Supriatmo, I.Z. Lubis.
Comparing sleep disorders in urban and suburban adolescents.
Paediatr Indones, 54 (2014), pp. 299-304
[35]
A. Grao-Cruces, A. Nuviala, A. Fernández-Martínez, A.M. Porcel-Galvez, J.E. Moral-Garcia, E.J. Martinez-Lopez.
Adherence to the Mediterranean diet in rural and urban adolescents of southern Spain, life satisfaction, anthropometry, and physical and sedentary activities.
Nutr Hosp, 28 (2013), pp. 1129-1135
[36]
K.A. Bernsdorf, C.J. Lau, A.H. Andreasen, U. Toft, M. Lykke, C. Glümer.
Accessibility of fast food outlets is associated with fast food intake. A study in the Capital Region of Denmark.
Health Place, 48 (2017), pp. 102-110

Please cite this article as: Boraita RJ, Alsina DA, Ibort EG, Torres JMD. Hábitos y calidad de vida relacionada con la salud: diferencias entre adolescentes de entornos rurales y urbanos. An Pediatr (Barc). 2022;96:196–202.

Copyright © 2022. Asociación Española de Pediatría
Idiomas
Anales de Pediatría (English Edition)

Subscribe to our newsletter

Article options
Tools
es en

¿Es usted profesional sanitario apto para prescribir o dispensar medicamentos?

Are you a health professional able to prescribe or dispense drugs?